Data_Exploration
# Look at number of data points for each gear type
log_2021 %>%
group_by(grcde_sum) %>%
count()## # A tibble: 3 × 2
## # Groups: grcde_sum [3]
## grcde_sum n
## <chr> <int>
## 1 LL 3009
## 2 PT 3756
## 3 SP 2913# also look at this from a region perspective
log_2021 %>%
group_by(grcde_sum, area) %>%
count()## # A tibble: 18 × 3
## # Groups: grcde_sum, area [18]
## grcde_sum area n
## <chr> <chr> <int>
## 1 LL Aleutian Islands 334
## 2 LL Bering Sea 17
## 3 LL Central Gulf of Alaska 634
## 4 LL East Yakutat / Southeast Alaska 1276
## 5 LL West Yakutat 705
## 6 LL Western Gulf of Alaska 43
## 7 PT Aleutian Islands 59
## 8 PT Bering Sea 138
## 9 PT Central Gulf of Alaska 2334
## 10 PT East Yakutat / Southeast Alaska 331
## 11 PT West Yakutat 605
## 12 PT Western Gulf of Alaska 289
## 13 SP Aleutian Islands 5
## 14 SP Bering Sea 164
## 15 SP Central Gulf of Alaska 1197
## 16 SP East Yakutat / Southeast Alaska 542
## 17 SP West Yakutat 774
## 18 SP Western Gulf of Alaska 231Note that LL = Longline/HAL, Pot = Rigid, SP = Slinky
ggplot(ak) +
geom_sf() +
stat_density_2d(log_2021, mapping = aes(x = AdjLon, y = lat2,
fill = log(..level..)),
geom = "polygon") +
facet_wrap(~grcde_sum, ncol = 1) +
scale_fill_viridis_c() +
labs(fill = "Kernel density of fishing") +
theme_bw()
For some of these, I combined the rigid and slinky pots into one category
ggplot(log_2021, aes(x = bottom_depth, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
scale_fill_colorblind() +
theme_bw() 
# depth aggregated
ggplot(log_2021, aes(x = bottom_depth, fill = gr_pot_comb)) +
geom_density(alpha = 0.75) +
scale_fill_colorblind() +
theme_bw() 
# depth by region
ggplot(log_2021, aes(x = bottom_depth, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
scale_fill_colorblind() +
facet_wrap(~area) +
theme_bw() 
# combined gear
ggplot(log_2021, aes(x = bottom_depth, fill = gr_pot_comb)) +
geom_density(alpha = 0.75) +
scale_fill_colorblind() +
facet_wrap(~area) +
theme_bw() 
- Retained weight = weight caught (kg)
- Retained fish = number of fish caught
- Retained weight / retained fish = weight per fish
# catch retained weight
ggplot(log_2021, aes(x = retained_wgt, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
scale_fill_colorblind() +
theme_bw() ## Warning: Removed 12 rows containing non-finite values (stat_density).
# catch retained numbers
ggplot(log_2021, aes(x = retained_fish, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
scale_fill_colorblind() +
theme_bw() ## Warning: Removed 5644 rows containing non-finite values (stat_density).
# retained catch in numbers broken up by regions
ggplot(log_2021, aes(x = retained_fish, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
scale_fill_colorblind() +
facet_wrap(~area, scales = 'free') +
theme_bw() ## Warning: Removed 5644 rows containing non-finite values (stat_density).
# retained catch in numbers broken up by regions
ggplot(log_2021, aes(x = retained_fish, fill = gr_pot_comb)) +
geom_density(alpha = 0.75) +
scale_fill_colorblind() +
facet_wrap(~area, scales = 'free') +
theme_bw() ## Warning: Removed 5644 rows containing non-finite values (stat_density).
# retained catch in weight broken up by regions
ggplot(log_2021, aes(x = retained_wgt, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
scale_fill_colorblind() +
facet_wrap(~area, scales = 'free') +
theme_bw() ## Warning: Removed 12 rows containing non-finite values (stat_density).
ggplot(log_2021, aes(x = retained_wgt, fill = gr_pot_comb)) +
geom_density(alpha = 0.75) +
scale_fill_colorblind() +
facet_wrap(~area, scales = 'free') +
theme_bw() ## Warning: Removed 12 rows containing non-finite values (stat_density).
# look at retained weight/retained fish (weight per fish)
# this hopefully may hep us get into potential size differences
# in contact selectivity
ggplot(log_2021, aes(x = retained_wgt / retained_fish, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
scale_fill_colorblind() +
labs(y = "weight per fish (kg)") +
theme_bw() ## Warning: Removed 5661 rows containing non-finite values (stat_density).
# break this up by region
ggplot(log_2021, aes(x = retained_wgt / retained_fish, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
facet_wrap(~area, scales = "free") +
scale_fill_colorblind() +
labs(y = "weight per fish") +
theme_bw() ## Warning: Removed 5661 rows containing non-finite values (stat_density).
# Regress retained weight/retained fish by bottom_depth
ggplot(log_2021, aes(x = bottom_depth, y =retained_wgt / retained_fish)) +
geom_point() +
geom_smooth() +
labs(y = "weight per fish") +
theme_bw() ## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 5661 rows containing non-finite values (stat_smooth).## Warning: Removed 5661 rows containing missing values (geom_point).
# break it up by region
ggplot(log_2021, aes(x = bottom_depth, y =retained_wgt / retained_fish,
color = area, fill = area)) +
geom_point(color = "grey") +
geom_smooth() +
scale_fill_colorblind() +
scale_color_colorblind() +
facet_wrap(~area) +
labs(y = "weight per fish") +
theme_bw() ## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 5661 rows containing non-finite values (stat_smooth).
## Removed 5661 rows containing missing values (geom_point).
# break it up by gear
ggplot(log_2021, aes(x = bottom_depth, y =retained_wgt / retained_fish,
color = grcde_sum, fill = grcde_sum)) +
geom_point(color = "grey") +
geom_smooth() +
scale_fill_colorblind() +
scale_color_colorblind() +
facet_wrap(~grcde_sum) +
labs(y = "weight per fish") +
theme_bw() ## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 5661 rows containing non-finite values (stat_smooth).
## Removed 5661 rows containing missing values (geom_point).
# break it up by gear and region
ggplot(log_2021, aes(x = bottom_depth, y =retained_wgt / retained_fish,
color = grcde_sum, fill = grcde_sum)) +
geom_point(color = "grey") +
geom_smooth() +
scale_fill_colorblind() +
scale_color_colorblind() +
facet_grid(grcde_sum~area) +
labs(y = "weight per fish") +
theme_bw() ## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 5661 rows containing non-finite values (stat_smooth).## Warning: Computation failed in `stat_smooth()`:
## x has insufficient unique values to support 10 knots: reduce k.
## Computation failed in `stat_smooth()`:
## x has insufficient unique values to support 10 knots: reduce k.## Warning: Removed 5661 rows containing missing values (geom_point).
# Repeat above, but combine slinky and rigid pots into one category
# break it up by gear
ggplot(log_2021, aes(x = bottom_depth, y =retained_wgt / retained_fish,
color = gr_pot_comb, fill = gr_pot_comb)) +
geom_point(color = "grey") +
scale_fill_colorblind() +
scale_color_colorblind() +
facet_wrap(~gr_pot_comb) +
labs(y = "weight per fish") +
theme_bw() ## Warning: Removed 5661 rows containing missing values (geom_point).
# break it up by gear and region
ggplot(log_2021, aes(x = bottom_depth, y =retained_wgt / retained_fish,
color = gr_pot_comb, fill = gr_pot_comb)) +
geom_point(color = "grey") +
geom_smooth() +
scale_fill_colorblind() +
scale_color_colorblind() +
facet_grid(gr_pot_comb~area) +
labs(y = "weight per fish") +
theme_bw()## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'## Warning: Removed 5661 rows containing non-finite values (stat_smooth).## Warning: Computation failed in `stat_smooth()`:
## x has insufficient unique values to support 10 knots: reduce k.
## Computation failed in `stat_smooth()`:
## x has insufficient unique values to support 10 knots: reduce k.## Warning: Removed 5661 rows containing missing values (geom_point).
# look at catch per skaate hauled
ggplot(log_2021, aes(x = retained_wgt / skates_hauled, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
coord_cartesian(xlim = c(0, 3000)) +
scale_fill_colorblind() +
theme_bw() ## Warning: Removed 12 rows containing non-finite values (stat_density).
# look at catch per skaate hauled combine pot
ggplot(log_2021, aes(x = retained_wgt / skates_hauled, fill = gr_pot_comb)) +
geom_density(alpha = 0.75) +
coord_cartesian(xlim = c(0, 3000)) +
scale_fill_colorblind() +
theme_bw() ## Warning: Removed 12 rows containing non-finite values (stat_density).
# break this catch per skate hauled by region
ggplot(log_2021, aes(x = retained_wgt / skates_hauled, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
coord_cartesian(xlim = c(0, 3000)) +
facet_wrap(~area, scale = "free_y") +
scale_fill_colorblind() +
theme_bw() ## Warning: Removed 12 rows containing non-finite values (stat_density).
# break this catch per skate hauled by region
ggplot(log_2021, aes(x = retained_wgt / skates_hauled, fill = gr_pot_comb)) +
geom_density(alpha = 0.75) +
coord_cartesian(xlim = c(0, 3000)) +
facet_wrap(~area, scale = "free_y") +
scale_fill_colorblind() +
theme_bw() ## Warning: Removed 12 rows containing non-finite values (stat_density).
- Skate Length = Length of each skate (not sure units)
- Vessel length (060 = over 60 ft), (U60 = under 60 ft)
# look at skate length aggregated
ggplot(log_2021, aes(x = skate_length, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
scale_fill_colorblind() +
# facet_wrap(~vessel_length, ncol = 1) +
theme_bw() ## Warning: Removed 80 rows containing non-finite values (stat_density).
# skate length by vessel length
ggplot(log_2021, aes(x = skate_length, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
scale_fill_colorblind() +
facet_wrap(~vessel_length, ncol = 1) +
theme_bw() ## Warning: Removed 80 rows containing non-finite values (stat_density).
# hook spacing / pot spacing
ggplot(log_2021, aes(x = hook_spacing, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
coord_cartesian(xlim = c(0, 500)) +
scale_fill_colorblind() +
labs(x = "hook spacing (m)") +
theme_bw() ## Warning: Removed 7 rows containing non-finite values (stat_density).
# total hooks / pots deployed
ggplot(log_2021, aes(x = total_hooks_pots, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
facet_wrap(~grcde_sum, scales = "free") +
scale_fill_colorblind() +
theme_bw() 
# skates hauled
ggplot(log_2021, aes(x = skates_hauled, fill = grcde_sum)) +
geom_density(alpha = 0.75) +
# facet_wrap(~grcde_sum, scales = "free") +
scale_fill_colorblind() +
theme_bw() 